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Moon Zoo is a citizen science project that utilises internet crowd-sourcingtechniques. Moon Zoo users are asked to review high spatial resolution imagesfrom the Lunar Reconnaissance Orbiter Camera (LROC), onboard NASAs LROspacecraft, and perform characterisation such as measuring impact crater sizesand identify morphological features of interest. The tasks are designed toaddress issues in lunar science and to aid future exploration of the Moon. Wehave tested various methodologies and parameters therein to interrogate andreduce the Moon Zoo crater location and size dataset against a validated expertsurvey. We chose the Apollo 17 region as a test area since it offers a broadrange of cratered terrains, including secondary-rich areas, older maria, anduplands. The assessment involved parallel testing in three key areas: (1)filtering of data to remove problematic mark-ups; (2) clustering methods ofmultiple notations per crater; and (3) derivation of alternative craterdegradation indices, based on the statistical variability of multiple notationsand the smoothness of local image structures. We compared differentcombinations of methods and parameters and assessed correlations betweenresulting crater summaries and the expert census.  We derived the optimal data reduction steps and settings of the existing MoonZoo crater data to agree with the expert census. Further, the regolith depthand crater degradation states derived from the data are also found to be inbroad agreement with other estimates for the Apollo 17 region. Our studysupports the validity of this citizen science project but also recommendsimprovements in key elements of the data acquisition planning and production.

The Moon Zoo citizen science project: Preliminary results for the Apollo 17 landing site